Theses and Dissertations Collection

Improving the resilience and safety of bridge structures continues to be of the utmost importance within the field of infrastructure engineering. A comprehensive understanding of bridge responses to different scenarios, such as unanticipated impact accidents from over-height trucks and increased traffic loads resulting from the implementation of new technologies, is essential to achieve this goal.

Accidental collisions between over-height trucks that exceed the vertical clearance limit and bridge superstructures happen all the time, often leading to compromised girders. Such incidents have far-reaching consequences for structural safety and performance. In current design codes, vehicular collision is often classified as an accidental load condition for bridge superstructures. However, how collision is addressed in design standards varies, and such recommendations are usually not comprehensive enough to allow for rigorous design. This study aimed to developing large-scale high-fidelity finite element models, using LS-DYNA, to fully understand the complex dynamic response of prestressed girder bridges under impact loads. Split Hopkinson Tensile Bar (SHTB) tests were performed on low-relaxation grade 270 prestressing strands at high strain rates to help in the calibration of our material models. The findings indicate that the proposed modeling technique can be effectively used to investigate the structural response of prestressed girder bridges subjected to lateral impact loads. Furthermore, the study identified two different damage responses, global damage and local damage failure, each with its own set of patterns such as longitudinal cracks, diagonal cracks, shear push-out, concrete spalling, and strands' cutting to failure. The asymmetrical loss of prestressing strands commonly observed in collision accidents induces a rotation of the section's primary axes. As a result, the girder's capacity to resist the moment applied about its geometric horizontal axis will be lowered beyond what is predicted by standard uniaxial section analysis, resulting in significant changes in the live load distribution factors. The observed changes in distribution factors may cause the interior girder to be overloaded compared to their design loads; requiring further considerations.

The operational characteristics of freight shipment will change significantly after the implementation of Autonomous and Connected Trucks (ACT) technology. This change will remarkably impact mobility, safety, and infrastructure service life. The platooning configuration enables trucks to be connected with themselves and the surrounding infrastructure. This arrangement has shown to be a promising solution to improve vehicles’ fuel efficiency, reduce carbon dioxide emissions, reduce traffic congestion, and improve transportation service. However, platooning may accelerate the damage accumulation of pavement and bridge structures due to the formation of multiple load axles within each platoon since those structures were not designed for such loads. According to AASHTO, bridges are designed based on a notional live load model comprised of one or two trucks per lane in conjunction with or separate from an applied uniform load. This damage, if accumulated, will cost the government billions of dollars to fix and will affect the mobility of people and goods. The potential damage to infrastructure may arise due to various factors such as the number of trucks in a platoon, gap spacing between trucks, and the type of trucks. This research work includes a thorough parametric study with 295,200 computer simulations using the commercial software SAP 2000. The goal was to evaluate the effect of different truck platooning configurations on the load rating of existing bridges. Overall, the number of trucks and their spacing have been shown to be critical parameters influencing bridge load ratings. The obtained results served as the dataset for training various machine learning models. The proposed machine learning model has shown its effectiveness in identifying optimal platooning configurations for bridge structures within the scope of the study.